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Since information theory was developed by Claude E. Shannon, in addition to its primary role in communications and networking, it has broadened to find applications in many other areas of science and technology, such as microeconomics, statistics, and neuroscience. This thesis investigates the application of information theoretic viewpoints to two interesting and significant topics. One is the fundamental topic in the field of communications and networking. The other is a long-term open issue in the area of microeconomics. We study the capacity of multiuser networks, which has been a long-standing problem in the information theory. Recently, Avestimehr, Diggavi, and Tse have proposed a deterministic network model to approximate multiuser wireless networks. For wireless multicast relay networks, they have shown that the capacity for the deterministic model is equal to the minimal rank of the incidence matrix of a certain cut between the source and any of the sinks. Their proposed code construction, however, is not guaranteed to be efficient and may potentially involve an infinite block length. We propose an efficient linear code construction for the deterministic wireless relay network model. Unlike several previous coding schemes, we do not attempt to find flows in the network. Instead, for a layered network, we maintain an invariant where it is required that at each stage of the code construction, certain sets of codewords are linearly independent. We then apply ideas from information theory to solve a canonical problem in microeconomics with information constraints. Specifically, we analyze the problem of nonlinear pricing with limited information. Due to information constraints, the seller is limited to offering a menu with a finite number of choices to a continuum of buyers with a continuum of possible valuations. By revealing an underlying connection to the quantization in the information theory, we introduce the conditions which the optimal finite menu for the socially efficient and that for the revenue-maximizing mechanism must satisfy. In both cases, we provide an estimate of the loss resulting from using the finite menu. We then extend our nonlinear pricing model to multi-product environment where each buyer can purchase a variety of multiple goods at a time. His preference over these goods is represented by a multi-dimensional vector in some compact subset with a continuum of possible valuations. We generalize our results to multi-product environment via vector quantization. We discuss the benefit of bundling the consumer's preferences over multiple goods, and designing the finite menus jointly in higher dimensions. This benefit arises by using vector quantization methods that take advantage of the dimensionality, the shape of the marginal density function, and the correlation among the consumer's types over multiple products. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

To meet ongoing demands for mineral resource, the market is continuously evolving to address the challenges of hard rock mining. The concept of actuated disc cutting is one of the latest developments for hard rock mechanical excavation. While the literature on actuated disc cutting has enabled some fundamental understandings, there is still substantial uncertainty in evaluating actuated disc cutting induced fragmentations under different operational conditions. To fulfil these knowledge gaps, actuated disc cutting tests were conducted at various operational conditions in two rock types. Fragments were collected after each cutting test and further examined by two sets of laser scanning machine. Analysis of the force signal yielded three performance parameters known as mean force drop, chipping to crushing ratio and specific energy. Analysis of fragment size yielded four performance parameters known as the fractal dimension, coarseness index, total projected area, and specific projected area. Parametric studies evaluated the weighted contribution of key variables actuated disc cutting to the variations of these performance parameters. The result indicated that the geometry factor and actuation factor of actuated disc cutting contribute more than the penetration rate. Statistical modelling was conducted to simulate the accumulation of force drop and fragment size. Results indicated both force drop events and fragment size follow the Generalized Extreme Value (GEV) distribution. It was further concluded that actuated disc cutting induced fragmentation is dominated by brittle failure from a statistical perspective since GEV is often associated stress distribution for brittle failure. Further multivariate correlation further identified the correlations between performance parameters from the cutter/mechanical response and fragments. The result indicated that chipping produces coarse material, leading to a less complicated fragmentation, and less complicated fragmentation requires less energy input. Multiple regression analysis was further conducted to establish some empirical models for geometry factor, actuation factor and penetration rate based on all performance parameters. This was followed by a sensitivity study on the effect of performance parameters on the geometry factor, actuation factor and penetration rate of actuated disc cutting.

The focus of this thesis is on Density Driven Convection (DDC) in porous media. In the context of CO₂ storage in saline aquifers, DDC can enhance solubility trapping of CO₂ into formation brine. To better comprehend this, analogue fluid experiments are being performed. However, validated one-to-one simulations thereof that are easy to amend are lacking. Having such a numerical model available would help advance research and cut the associated costs. A numerical model of DDC in a porous medium has been developed using a commercially available software: COMSOL Multi-physics. This model is validated by comparing one-to-one simulation results of analogue fluid experiments performed in a bowl filled with beads. The bowl geometry is divided into a top- and bottom domain, which are initially filled with, respectively, a mixture of methanol & ethylene glycol (MEG) and water. Over time MEG dissolves in water and increases the fluid density at the interface. Eventually, it initiates DDC which speeds up the mixing process. This work furthermore details a predictive study where the bead diameter is varied (which in its turn changes the porous medium's permeability and hence also the Rayleigh number of the experiments). I found a linear relationship between the Sherwood number (Sh) and the Rayleigh number (Ra) i.e. Sh = 0.125Ra, however this result is strongly dependent and sensitive to the choice of the constant flux regime at a given Ra. When the peak values of the flux j/j_dif are considered, I find another linear relationship with Ra i.e. j/j_dif(peak) = 0.139Ra. In this dissertation, I included a comparison between 2D and 3D simulations as well as different geometries (i.e. bowl, block and cylinder). Moreover, I discuss the effect of the orientation of layering in the aquifer, or experiment, relative to the gravity direction at an angle θ. Finally, I show the effects of various viscosity transition curves and mobility ratios have on DDC in a porous medium.

Cardiovascular diseases and ageing are two main challenges for health services. Cardiovascular disease is characterised by atherosclerosis, leading to heart attack and stroke. Atherosclerosis is a focal disease and occurs preferentially in regions of arterial bifurcation and curvature where complex flow features are observed. The carotid arteries represent a region of significant involvement in atherosclerosis. Previous studies have shown that haemodynamic factors are important determinants of the local distribution of atherosclerosis. However, longitudinal studies are lacking. The aim of this study was to investigate age-related changes in carotid artery morphology and haemodynamics based on longitudinal data acquired from a group of middle-aged subjects recruited to a cardiovascular disease prevention programme in Italy. The longitudinal study started in 1996 and participants were examined twice 12 years apart. All subjects underwent blood viscosity measurements and echo-Doppler examinations of the common carotid artery at baseline and follow-up. From the acquired ultrasound data, common carotid artery diameter, blood flow velocity, and intima-media thickness were measured, and wall shear stress, circumferential wall tension and Peterson elastic modulus were calculated. It was found that with ageing, blood viscosity increased, common carotid artery diameter increased, mean blood velocity and wall shear stress decreased, while intima-media thickness, circumferential wall tension and arterial stiffness increased. Interrelationships of the data were also examined: reductions in common carotid wall shear stress were independently associated with intima-media thickening. Furthermore, ageing-associated wall shear stress reduction predicted the development of atherosclerotic plaques, independently of known cardiovascular risk factors. In addition, in participants presenting shear stress reductions in only one side of the common carotid artery, development of atherosclerosis in the carotid tree was limited to the same body side. In conclusion, this longitudinal study confirms the role of arterial wall shear stress as a mediator of the effects of ageing on atherosclerosis.

This dissertation examines whether US exporters of agricultural commodities, including wheat, beef, pork, corn, soybean and lettuce, price to market in both a monopolistic and an oligopolistic framework. In a static monopolistic framework, considering the seasonality characteristics of prices and costs of agricultural products, a seasonal error correction model (SECM) is estimated. This study is the first one to apply the concepts of seasonal cointegration and seasonal common trends. In cases where seasonal cointegration is rejected by the hypothesis test, a vector error correction model (VECM) is used. The results from the cointegration method confirm strong imperfect competition and destination-specific characteristics of PTM behavior. Different price responses imply that under depreciations of the US dollar, exports to Japan, Canada, and the Philippines will increase but have a smaller effect on improving the US trade balance than in the case of perfect competition, while exports to South Korea, Mexico, Singapore, and Hong Kong will increase by a relatively small percentage, which results in an ambiguous impact on the US trade balance. In an oligopolistic framework, this study distinguishes different roles of the two exchange rates in export pricing strategies. The results show that imperfect competition exists in US wheat, beef, pork, and corn export markets. For beef, pork, and corn exports, the objective of US exporters is to keep local currency prices stable, which to some extent mitigates the export-enhancing effect of depreciations of the US dollar. The exceptional case is US wheat exports. Taking into account the huge export subsidies that US wheat exporters receive from the US Export Enhancement Program (EEP), US agricultural exporters tend to keep price-stabilizing strategies unless strong financial support from the government is available. Therefore, the depreciation of the US dollar is not sufficient for improving the US agricultural trade balance without governmental export supports. The real exchange rate exhibits a strong price-enhancing effect on export prices in most selected products except wheat, after the effect of the nominal exchange rate is taken into account.

Cellulosic biomass is one of the most abundant materials on earth, making it an attractive prospect for bioprocessing to produce fuels and chemicals as an alternative to fossil fuels. Traditional processes that convert cellulose to products do so via an inefficient multistep process, involving sequential reactors that first hydrolyse the cellulose through the addition of exogenous enzymes and then pass the hydrolysate to the next reactor for the liberated sugars to be fermented. Consolidated bioprocessing (CBP) combines this two-step process into one, offering improvements in costing, by removing the need for extra reactors, and efficiency, by having organisms utilise sugars as they are produced reducing end product inhibition of the cellulases. This thesis is aims to model the CBP process by developing separate hydrolysis and fermentation models and then integrating them together. Then by using the model the optimal conditions for ethanol production will be found and the limiting steps of the process identified. A model depicting the breakdown of cellulose by cellulases and a dynamic metabolic flux analysis (DMFA) model describing the fermentation of glucose and cellobiose by the thermophilic organism G. thermoglucosidasius was developed. These models were fitted to experimental data of the cells growing on cellobiose and literature data of cellulose hydrolysis. The effects of the timing of the anaerobic switch, adding either glucose or cellobiose to the system and enzyme composition were analysed. It was found that by adding 5 mmol/L of cellobiose at the start of the reaction, the ethanol production increased by 35% (mol/mol). The timing of the switch from aerobic to anaerobic conditions was found to be an important factor. The later the switch occurred, the less ethanol was produced. The longer the cells lived in aerobic conditions the more of the glucose and cellobiose was used for cell growth, leaving less for ethanol production once the switch was made. The ratio of endo/exoglucanses to β-glucosidase affected the rate at which cellulose was broken down. This effect then passed on to the cell growth curves and ethanol production. A ratio of 0.95 exo/endoglucanases to 0.05 β-glucosidases was found to produce the most ethanol. A combination of 1-hour anaerobic switch time, 0.95/0.05 enzyme split and 5 mmol/L initial cellobiose were found to be optimal, producing 115 mmol/L of ethanol. Global sensitivity analysis (GSA) was carried out on each of the models, with the key parameters affecting the outputs identified. There was a lack of detailed CBP for these cells growing on cellulose to assess the accuracy and validate the model. Therefore, there are areas of the model that require further investigation, in particular how the model predicts cell growth. Despite this the model does show that the ability to test changes to the process through simulations can be very powerful. Modelling the CBP process opens areas for more research in the future, such as online optimisation and control. Accurate control of co-cultures of microorganisms will be key in the future to produce exact levels of enzyme production and cell growth that maximise the production of products.

In this work, we developed and applied computational methods for simulating flow, transport and reactive transport in porous media. This comprised four main components: single-phase flow calculation; chemical transport calculation; the coupling to reaction kinetics at mineral surfaces and resulting structural changes; and the use of parallel and GPU computing to make the calculation practicable on realistic rock geometries. Single phase flow was calculated using the Lattice Boltzmann (LB) method. We used the multi-relaxation-time (MRT) operator for its superior stability and viscosity-independence. A sparse memory approach was employed which improves the efficiency of calculations performed on low-permeability rock pore-space images. We also extended an idea proposed by Skordos in which the lattice Boltzmann densities were transformed to increase the number of floating point bits retained in the calculation. We showed that this enhances the numerical precision of the calculation considerably, where the original paper found no appreciable benefit. We showed how this now permits the 4-byte datatype to be used reliably in slow flowing, heterogeneous domains. The LB algorithm was implemented for the use of parallel GPUs (Graphics Processors) using the MPI (Message Passing Interface) and shown to give strong scaling on a cluster of 24 Tesla K40 GPUs. A study of single phase permeability on micro-CT images of sandstone and carbonate rock pore structures of varying degrees of heterogeneity was carried out. Good agreement with experiment was found for the simpler pore spaces, while discrepancies in the micro-porous samples was attributed to two causes: 1) the exclusion of flow through unresolved micro-porosity and 2) unrepresentative sample sizes used in the simulation. The effect of image resolution and segmentation was studied by comparing single phase permeability computed in 1) scans of the same volume obtained at different voxel sizes, individually segmented and 2) numerically coarsened images from a high resolution segmented image. Numerical coarsening from a high resolution segmented image was found to be much more consistent than 1) and was shown to preserve porosity and permeability down to lower voxel size images unlike the images scanned and segmented at different voxel sizes. Finally, representative elementary volume (REV) was investigated for the rock samples. A statistical method was used in which porosity and permeability were obtained from sub-volumes sampled from the domain. The convergence of these parameters with sub-volume size was used to obtain characteristic length scales and measures of heterogeneity. The image sizes used were found to be unrepresentative for the complex microporous carbonates. Transport curves (propagators) were computed in three different porous media samples of increasing heterogeneity (a bead-pack; sandstone; and carbonate) and found to agree with experiment. Questions about the origins of stagnant transport zones in the microporous carbonate were pursued by investigating the effects of image segmentation. The effects of the image segmentation techniques, in which grey-scale micro-porosity in a scanned pore image is binarised into fluid or mineral, were quantified by computing the fraction of trapped solute (stagnant zones) for segmentations of varying porosity. Physical differences between experiment and calculation were clarified, and we suggest alternative approaches for the treatment of micro-porous rocks. A pore-scale reactive flow model was put together by coupling flow calculation and solute transport methods with changes in pore-structure through chemical kinetics. Convection and diffusion in this model was solved using a finite-volume approach: a second order transport model with a flux limiter function made the model suitable for high Peclet number transport calculations. We also proposed a method for counteracting errors associated with the staircase representation of diagonal surfaces in the Cartesian grid in which exposed grid surfaces are associated with a rescaling factor. First order reaction kinetics were included at mineral surfaces and the dissolution of a sphere was shown to give different dissolution profiles with different dimensionless transport and reaction parameters. The dissolution model was applied to the reaction between HCl acid and calcite mineral under the assumption that products of the reaction could be neglected. An experimental system in which HCl acid was injected through a flow cell containing a calcite block was simulated and the normalised volume of undissolved calcite was compared with the experimental data, as well as resulting morphologies obtained by micro-CT scanning. Good agreement with the experimental dissolution rate was obtained, however some differences in the resulting morphologies were found. This was attributed to neglecting the influence of product ions on the diffusion behaviour of the reactant and was discussed. By obtaining the concentration of H+ reactant on the surface of calcite block, the process could be concluded to be strongly transport-controlled. This enabled the definition of a new effective Damkohler number in terms of the reactant surface concentration which no longer required approximating length scales or separating convection or diffusion rates. Finally, the dissolution of a Ketton carbonate sample was computed. The injection process mirrored that of a strong acid flowing through the pore-space at a given flow rate, and having an intrinsic surface reaction rate with the rock mineral. It was found that the flow rate strongly affected the resulting dissolution pattern, in line with experimental observation. This lead to drastically altered flow properties, including single-phase permeability which was quantified.

The world's water shortage problem has drawn immense attention and many researchers have tried to solve the problem by introducing water purification and seawater desalination. It is widely accepted that a reverse osmosis (RO) process is more effective in terms of separation capability and its simple installation and requires less energy than any other water purification and seawater desalination processes. However, its specific energy consumption is still higher than the theoretical minimum energy and there is scope for further improvement. Spiral wound modules are the most commonly used in large RO desalination plants, in which flat sheet membranes and spacers are alternately arranged and wrapped around a centre pipe. Feed spacers play an important role by keeping membrane sheets separate and enhancing mixing near membrane surfaces. This thesis focusses on identifying opportunities for enhancement of membrane performance, reductions in energy consumption and other costs via predictive modelling and model-based scenario studies. Firstly, a new mathematical model for a spiral wound module is developed by accounting for its unique geometric features. The performance of the spiral model is compared with existing models based on the plate-and-frame approach. The spiral model is then used to investigate the effects of geometric parameters on module performance and energy consumption, and further extended to simulate a large-scale RO process with multiple modules. Secondly, computational fluid dynamics (CFD) models for spacer-filled feed channels are built using two-dimensional geometric representations and simulated under a wide range of operating and geometric conditions. A new boundary condition is introduced in the CFD models by reformulating the solution-diffusion model in order to describe permeable membrane walls. As a result, the effects of different operating and geometric conditions in the presence of spacers can be assessed in terms of key performance indicators such as water flux, concentration polarisation modulus and pressure drop. A large number of numerical simulations have been carried out and the results are used to derive empirical correlations for concentration polarisation and pressure loss in a feed channel, in order to facilitate the incorporation of the impact of spacers in a process model. The new correlations are implemented in a process model and compared with existing correlations that were experimentally derived in terms of predicted performance and energy consumption. Finally, three-dimensional CFD models for various spacer designs are developed by varying filament configuration, mesh angle and flow attack angle. By implementing the proposed boundary condition for permeable membrane walls, the CFD models presented here can be utilised to predict membrane performance for a given feed spacer type and geometry.

The human aorta is often affected by many cardiovascular diseases, including atherosclerosis, aneurysm and dissection. There is considerable evidence suggesting that these diseases are associated with the morphology and haemodynamic functions of the aorta, but not all these parameters can be measured directly in vivo. In particular, the helical flow characteristics and haemodynamic wall parameters can only be evaluated from quantitative information on a flow field resolved both in space and time. This study provides a comprehensive analysis of geometric and haemodynamic characteristics of the human aorta through subject-specific simulations of blood flow based on medical images. Computational fluid dynamics (CFD) models of the thoracic aorta were developed based on in vivo anatomical and flow data acquired using magnetic resonance imaging (MRI). In order to capture potential transitional and turbulent flow in the aorta, the correlation based shear stress transporttransitional (SST-Trans) turbulence model was employed. Detailed flow analyses were performed on multiple cases of normal thoracic aortas with a tricuspid aortic valve (TAV) and abnormal aorta with a bicuspid aortic valve (BAV). Results obtained from this study gave quantitative insights into the flow distributions and wall shear stress (WSS) patterns in normal and abnormal aortas. Morphological features and flow patterns of the TAV and BAV aortas were compared. In addition to standard flow parameters, specific indices were evaluated to allow for direct comparisons between the two groups; these included flow reversal ratio (FRR), helicity flow index (HFI) and shear range index (SRI). The results showed that all examined aortas tapered from the proximal ascending segment to the distal descending segment, with the BAV aorta showing a more distinct tapering. Although flow patterns were qualitatively similar in the TAV and BAV aortas, there were substantial quantitative variations. Highly disturbed flow was observed in all examined aortas during part of the cycle, mostly in the systolic deceleration phase. Predicted WSS was higher in the TAV aorta than in the BAV aorta, with the highest WSS occurring in regions around the major arch branches. Comparisons between the predicted and measured velocities showed a good agreement, demonstrating that MR image-based CFD modelling methodology can be used to obtain reliable haemodynamic parameters that are important in clinical assessment and management of aortic diseases.

Background Chronic venous disease is a common, distressing and significant cause of health care expense. There have been few developments in the treatment of deep venous disease as the understanding of the clinical and pathophysiological significance of deep vein reflux and valve failure remains poor. Previous attempts to develop a prosthetic vein valve implant have been disappointing. Difficulties with early thrombosis led researchers to abandon their efforts many years ago. Attempts to create a valve implant should be revisited. Aims The aims of this project are to: evaluate variables around normal deep vein valves, to develop validated computational and laboratory flow models for deep venous function, and to develop and investigate a novel material to engineer a prototype bioprosthetic deep vein valve replacement. Methods Functional Anatomy: This is a prospective observational study evaluating subjects with normal deep veins. B and M Mode ultrasound, contrast (microbubble) enhanced ultrasound and dynamic magnetic resonance imaging of normal subjects was carried out. This has given the flow, velocity data and anatomical images required for the project. Modelling: A preliminary computational flow model has been developed using the data obtained from the imaging stage of the project. This is a 2-dimensional model incorprating flexible valve leaflets. A laboratory model of venous function, in the form of a flow rig has been created. Materials: Presently, polymers and polymer coated metal stents, used in the vascular system have several problems: they are very thrombogenic and they lack haemocompatibilty and biocompatibility, in addition they lack the required mechanical properties. A novel material that is biocompatible, a copolymer of methacrylolyoxyethyl phosphorylcholine (MPC), trimethylsilyl-2-propyl methacrylate (TMSPMA) and Hydroxypropyl methacrylate (HPMA), has been synthesised. Its properties have been modified by electrospinning and crosslinking to change its solubility and mechanical properties, without altering its biocompatibility. Impact This project aims to guide the development of a treatment for patients, for whom few options are available. Chronic venous disease and venous ulceration are painful and debilitating, potentially requiring years of treatment. Effective, minimally invasive treatment options could result in accelerated ulcer healing and improvements in symptoms and quality of life as well as reduced costs.

Background: Aortic stiffness as measured by pulse wave velocity (PWV) is a predictor of cardiovascular disease and other outcomes in different diseased and healthy populations, independent of traditional risk factors. The relationships between PWV measurement, global functional outcome and injury to the brain, kidney, and heart have never been examined in cardiac surgery patients. Objective: The objective of this project was to assess the relationship between aortic stiffness and health related quality of life (QoL), cognitive function, acute kidney injury (AKI), and cardiac function in patients undergoing aortic valve replacement (AVR). Methods: Aortic PWV, QoL, cognitive function, left ventricular (LV) function and NYHA class were assessed pre- and post-operatively (409 ± 159 days). The brain injury biomarker, N-methyl-D-aspartate receptor antibody (NR2Ab), was measured pre-operatively only. The biomarker of myocardial strain, B-type natriuretic peptide (BNP), and the novel AKI biomarker, neutrophil gelatinase-associated lipocalin (NGAL), were measured pre-operatively, and at 3 h and 18-24 h post-CPB. Results: Fifty-six patients (16 females; mean age, 71 ± 8.4 years) were included in this study, of which 50 (89%) patients attended the follow-up visit. No relationship was found between the degree of aortic stenosis (AS) and PWV, and AVR had no effect on aortic stiffness post-operatively. QoL and NYHA class significantly improved, while cognitive function did not deteriorate after AVR. High PWV is independently related to poorer QoL, cognitive function levels and NYHA class both pre- and post-operatively. PWV was not related to LV function, BNP or NGAL levels, but it was independently related to the level of NR2Ab. PWV did not correlate with AKI which was developed in 30% of the cases. Early post-operative plasma level of NGAL is the earliest predictive marker of post-operative AKI and the need for early medical renal intervention. Pre-operative BNP level was significantly and negatively correlated with pre-operative LV function, AS (valve area), and NYHA class in the post-operative follow-up period. Conclusion: In AVR patients, PWV is independently related to global functional status, cognitive function and brain injury biomarkers, but is not related to AKI or myocardial strain.

Embryonic stem cells (ESCs) are promising as therapeutic material since they are pluripotent (potentially differentiate into any mature cell) and have “limitless” self-renewal capacity. To achieve widespread clinical utility, ESC cultures have to be designed to meet specific process requirements (e.g. quantity, quality etc.). Currently, most pluripotent stem cell (PSC) cultures are fragmented protocols relying on operator–intensive processing, as 2D monolayers on tissue culture plastic, at ambient O2 conditions. Incidentally, such culture conditions are sub-optimal, often leading to unscheduled stem cell behaviour. This thesis examines how ESC bioprocesses can be improved. Culture environment effects on ESCs are investigated, as well as computational tools for in silico design. I demonstrate how critical culture parameters and mathematical modelling can be exploited to improve the undifferentiated expansion of ESCs. Beginning with 3D murine ESCs (mESCs) cultures, 1) dynamic rotary cultures were demonstrated to improve self-renewal signalling activity, yielding improved proliferation of mESCs with higher “stemness” levels. 2) Culture metabolism was another critical factor. During batch feeding, metabolites accumulate within the culture environment especially at later stages in culture, causing stresses that impair ESC proliferation and “stemness”, independent of growth factor levels. In contrast, perfusion feeding maintained well-regulated culture environments that promoted the expansion of highly “naïve” mESCs. 3) Computational approaches can complement bioprocess design. Mathematical models identified novel multi-scale interactions within the bioprocess and effectively simulated bioreactor fluid dynamics. 4) As a means to further optimize the bioprocess, alternative signalling factors were combined with dynamic perfusion cultures in reduced (5%) O2 conditions, which generated increased cell yields having high “stemness” levels at half the costs. In conclusion, numerous ‘standard’ culture conditions were found to be sub-optimal for mESC culture, emphasizing the need for improved bioprocesses using rational design based on stem cell bioscience. It is anticipated that these integrated stem cell bioprocesses, can improve product yield and quality at reduced costs. Such bioprocess strategies will facilitate the usage of PSCs as therapeutics.